A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (<i>Aedes albopictus</i>)

Shabani, Farzin; Tehrany, Mahyat Shafapour; Solhjouy‐Fard, Samaneh; Kumar, Lalit

doi:10.7717/peerj.4474

Cited by 19 publications

(11 citation statements)

References 61 publications

(66 reference statements)

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“…Comparative analysis means to seek and explain the similarity and differences between subject. It is common to use in particular research project (8)(9)(10). In this study comparative analysis was carried out for a period of 7 years, from 2010 to 2016.…”

Section: Methodsmentioning

confidence: 99%

Dengue Hemorrhagic Fever Incidence Trend of the 2010-2016 Period in Indonesia

Purwanti¹,

Sudaryanto²,

Hartanto³

et al. 2019

ATMPH

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Indonesia is a country with endemic Dengue Hemorrhagic Fever (DHF) disease because it is located in the tropical region which is the living habitat of Aedes Aegepty mosquitoes. The existence of DHF disease in Indonesia makes this problem one of the things that need to be considered about health problems in Indonesia. ObjectivesThis study was to explore the trend of DHF in Indonesia from 2010 to 2016. MethodsThe design of this study was a retrospective study using secondary data available from The Ministry of Health report. The DHF disease data of 34 provinces were analyzed by temporal trend and comparative analysis. Results

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Section: Methodsmentioning

confidence: 99%

Dengue Hemorrhagic Fever Incidence Trend of the 2010-2016 Period in Indonesia

Purwanti¹,

Sudaryanto²,

Hartanto³

et al. 2019

ATMPH

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“…This software is often used for modeling species distribution, and effectively handles a small number of collection sites [38][39][40][41][42]. Based on the review, we selected 18 environmental variables which had a permutation importance (PI) of at least 5% (Table 2) [34,[43][44][45][46][47][48][49][50][51][52][53][54][55]. PI indicates the importance of each variable in a MaxEnt model [56].…”

Section: Environmental Variablesmentioning

confidence: 99%

Geographic distribution and future expansion ofAedes albopictusin the Democratic Republic of the Congo

Vulu

Bobanga

Sunahara

et al. 2021

Preprint

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Aedes albopictus with an Asian origin has been reported from central African countries. The establishment of this mosquito species poses a serious threat as the vector of various infectious diseases. Since information about Ae. albopictus in Democratic Republic of the Congo (DRC) is scarce, we investigated the current distribution of this mosquito species. Based on the factors affecting the distribution, we predicted future distribution. We conduced entomological surveys in Kinshasa and three neighboring cities from May 2017 to September 2019. The survey was extended to seven inland cities. A total of 19 environmental variables were examined using the maximum entropy method to identify areas suitable for Ae. albopictus to establish a population. We found Ae. albopictus at 21 of 23 sites in Kinshasa and three neighboring cities. For the first time Ae. albopictus was also found from three of seven inland cities, while it was not found in four cities located in the eastern and southeastern parts of DRC. A maximum entropy model revealed that the occurrence of Ae. albopictus was positively associated with maximum temperature of the warmest month, and negatively associated with wider mean diurnal temperature range and enhanced vegetation index. The model predicted that most parts of DRC are suitable for the establishment of the mosquito. The unsuitable areas were the eastern and southeastern highlands, which have low temperatures and long dry seasons. We confirmed that Ae. albopictus is well established in Kinshasa and its neighboring cities. The expansion of Ae. albopictus to the inland is ongoing, and in the future the mosquito may establish in most parts of DRC.

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“…For our analysis, the quantile method suited the classification of the extent of habitat loss and gain relative to the present. The method is effective for the classification of areas, moving equal quantities of pixels into each group without separation difficulties (Shabani et al 2018). There are four main quantile methods (natural breaks, equal intervals, geometrical intervals and standard deviations) available for classifying scaled data (Ayalew et al 2004, Ayalew and Yamagishi 2005, Papadopoulou-Vrynioti et al 2013, Tehrany et al 2017, with the appropriate method depending on the type of data and their application.…”

Section: Species Distribution Modellingmentioning

confidence: 99%

Climate‐driven shifts in the distribution of koala‐browse species from the Last Interglacial to the near future

et al. 2019

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The koala's Phascolarctos cinereus distribution is currently restricted to eastern and south‐eastern Australia. However, fossil records dating from 70 ± 4 ka (ka = 103 yr) from south‐western Australia and the Nullarbor Plain are evidence of subpopulation extinctions in the southwest at least after the Last Interglacial (~128–116 ka). We hypothesize that koala sub‐population extinctions resulted from the eastward retraction of the koala's main browse species in response to unsuitable climatic conditions. We further posit a general reduction in the distribution of main koala‐browse trees in the near future in response climate change. We modelled 60 koala‐browse species and constructed a set of correlative species distribution models for five time periods: Last Interglacial (~128–116 ka), Last Glacial Maximum (~23–19 ka), Mid‐Holocene (~7–5 ka), present (interpolations of observed data, representative of 1960–1990), and 2070. We based our projections on five hindcasts and one forecast of climatic variables extracted from WorldClim based on two general circulation models (considering the most pessimistic scenario of high greenhouse‐gas emissions) and topsoil clay fraction. We used 17 dates of koala fossil specimens identified as reliable from 70 (± 4) to 535 (± 49) ka, with the last appearance of koalas at 70 ka in the southwest. The main simulated koala‐browse species were at their greatest modelled extent of suitability during the Last Glacial Maximum, with the greatest loss of koala habitat occurring between the Mid‐Holocene and the present. We predict a similar habitat loss between the present and 2070. The spatial patterns of habitat change support our hypothesis that koala extinctions in the southwest, Nullarbor Plain and central South Australia resulted from the eastward retraction of the dominant koala‐browse species in response to long‐term climate changes. Future climate patterns will likely increase the extinction risk of koalas in their remaining eastern ranges.

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A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

Cited by 19 publications

References 61 publications

Dengue Hemorrhagic Fever Incidence Trend of the 2010-2016 Period in Indonesia

Dengue Hemorrhagic Fever Incidence Trend of the 2010-2016 Period in Indonesia

Geographic distribution and future expansion ofAedes albopictusin the Democratic Republic of the Congo

Climate‐driven shifts in the distribution of koala‐browse species from the Last Interglacial to the near future

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